PROJECT SUMMARY (See instructions); The underlying hypothesis of this application is that critical molecular features of host-pathogen interactions and responses dictate the pathogenic outcome of viral infection. Thus, a comprehensive understanding of viral-host interactions, innate responses to viral infection, and viral evasion strategies is pivotal for predictive modeling of viral pathogenesis. Here, we will provide a comprehensive overview ofthe genetic, chemical, and biochemical networks that play a role in controlling influenza virus infection by investigating host-virus interactions in an ex vivo setting using primary human cells. The impact of influenza virus replication on the host will be studied using next generation sequencing technologies to interrogate cellular RNA populations to define transcriptome-level changes (RNA-seq), conduct genome-wide survey of promoters engaged by RNA polymerase (GRO-seq), as well as evaluate epigenetic alterations in the chromosomal landscape (CHiP-seq). Furthermore, global alterations in intracellular and extracellular metabolite levels, protein abundance, as well as post-translational modifications induced upon viral infection will be measured. Combining these approaches with genome-wide functional genomic screening and high-throughput protein interactome analysis will enable the generation of high-resolution networks that accurately depict the hierarchies of interactions between influenza virus and the host. By conducting these analyses simultaneously with three viruses that drive varying pathogenic outcomes, computational modeling of these data will enable us to identify critical nodes ofthe viral-host network that are predictive of viral pathogenesis. The in vivo and clinical impact of these nodes will be evaluated in Projects 2 and 3, respectively.